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---
language:
- mn
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-cased-ner-demo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-multilingual-cased-ner-demo
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1333
- Precision: 0.9160
- Recall: 0.9229
- F1: 0.9194
- Accuracy: 0.9779
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1658 | 1.0 | 572 | 0.1113 | 0.8581 | 0.8792 | 0.8685 | 0.9658 |
| 0.0816 | 2.0 | 1144 | 0.0880 | 0.8950 | 0.9096 | 0.9022 | 0.9737 |
| 0.0554 | 3.0 | 1716 | 0.0935 | 0.8941 | 0.9096 | 0.9018 | 0.9741 |
| 0.0394 | 4.0 | 2288 | 0.1069 | 0.9070 | 0.9189 | 0.9129 | 0.9762 |
| 0.0284 | 5.0 | 2860 | 0.1029 | 0.9007 | 0.9184 | 0.9095 | 0.9752 |
| 0.0192 | 6.0 | 3432 | 0.1110 | 0.9102 | 0.9214 | 0.9157 | 0.9764 |
| 0.0139 | 7.0 | 4004 | 0.1156 | 0.9166 | 0.9272 | 0.9218 | 0.9786 |
| 0.0095 | 8.0 | 4576 | 0.1319 | 0.9091 | 0.9174 | 0.9132 | 0.9761 |
| 0.0066 | 9.0 | 5148 | 0.1313 | 0.9132 | 0.9226 | 0.9179 | 0.9781 |
| 0.0053 | 10.0 | 5720 | 0.1333 | 0.9160 | 0.9229 | 0.9194 | 0.9779 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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